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PubMed2004

Information about the logical structure of a category affects generalization.

This paper considers whether information about the logical structure of a category affects how people generalize. We carried out three experiments with the following structure: participants were first presented with a set of training items, and were subsequently asked to decide whether new items belonged to the same category as the training items. Each experiment had two conditions that differed only in terms of the category label provided for the training items; different category labels conveyed different information about the logical structure of the category to which the training items were supposed to belong. In all cases, participants' generalization was greatly affected by such information. Our results suggest that people make the default assumption that category labels correspond to groupings of highly similar objects.

Adult↗

PubMed2004

Fuzzy logic and causal reasoning with an 'n' of 1 for diagnosis and treatment of the stroke patient.

The current scientific model for clinical decision-making is founded on binary or Aristotelian logic, classical set theory and probability-based statistics. Evidence-based medicine has been established as the basis for clinical recommendations. There is a problem with this scientific model when the physician must diagnose and treat the individual patient. The problem is a paradox, which is that the scientific model of evidence-based medicine is based upon a hypothesis aimed at the group and therefore, any conclusions cannot be extrapolated but to a degree to the individual patient. This extrapolation is dependent upon the expertise of the physician. A fuzzy logic multivalued-based scientific model allows this expertise to be numerically represented and solves the clinical paradox of evidence-based medicine.

Evidence-Based Medicine↗

PubMed1998

Some logical functions of joint control.

Constructing a behavioral account of the language-related performances that characterize responding to logical and symbolic relations between stimuli is commonly viewed as a problem for the area of stimulus control. In response to this problem, the notion of joint control is presented here, and its ability to provide an interpretative account of these kinds of performances is explored. Joint control occurs when the currently rehearsed topography of a verbal operant, as evoked by one stimulus, is simultaneously evoked by another stimulus. This event, the onset of joint stimulus control by two stimuli over a common response topography, then sets the occasion for a response appropriate to this special relation between the stimuli. Although the mechanism described is simple, it seems to have broad explanatory properties. In what follows, these properties are applied to provide a behavioral interpretation of two sorts of fundamental, putatively cognitive, performances: those based on logical relations and those based on semantic relations. The first includes responding to generalized conceptual relations such as identity, order, relative size, distance, and orientation. The second includes responding to relations usually ascribed to word meaning. These include relations between words and objects, the specification of objects by words, name-object bidirectionality, and the recognition of objects from their description. Finally, as a preview of some further possibilities, the role of joint control in goal-oriented behavior is considered briefly.

Child Development↗

PubMed2006

Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.

Ammonia↗

PubMed1992

Extended normative data for the Logical Memory subtests of the Wechsler Memory Scale--Revised: responses from a sample of cognitively intact elderly medical patients.

66 cognitively intact geriatric medical patients (ages 70 to 99; M = 77 yr.) were given the Logical Memory subtests of the Wechsler Memory Scale--Revised to extend normative data. 43 women and 23 men, 35 white and 31 black persons made up this urban geriatric sample. A review of patients' medical histories and Mattis' Dementia Rating scores of 129 or greater were used to ensure a sample of cognitively intact patients. Analyses showed that Logical Memory scores were uncorrelated with education, race, sex, or age.

Aged↗

PubMed2000

Does logic moderate the fundamental attribution error?

The fundamental attribution error was investigated from an individual difference perspective. Mathematicians were compared with nonmathematicians (Exp. 1; n: 84), and undergraduates who scored high on a test of logical reasoning ability were compared with those who scored low (Exp. 2; n: 62). The mathematicians and those participants scoring higher on logic appeared less prone to the fundamental attribution error, primarily using a measure of confidence in attributions.

Adult↗

PubMed2001

Digital vision theory: Boolean logic model.

Guild (1932) stated the general requirements for processing signals in color vision system and a digital format of his paradigm is developed in this paper. The disk structure generates the digital receptor pulse. The input modalities form sets, linked by intersections, joins, and complement junctions. The synapses are elements in these junctions. Complex synapses form junctions to create Boolean logic processing. A computer program using these Boolean logic functions calculates: Light and dark adaptation responses; Color matching and spectral coordinate functions; Chromatic adaptation; Color shift responses; and Dynamic neural responses. These calculations compare favorably with the experimental data. The processing criteria for signals in the vision system are given by Guild (1932). The analysis in this paper uses his criteria to develop a model of the vision system. A computer program simulates the digital processing of signals from the external photon source to the neural output signals from the ganglion cells in the inner-plexiform layer. The responses are compared with the responses of actual vision systems.

Color Perception↗

PubMedDate not supplied

Digital vision theory: Boolean logic model.

Adaptation, Physiological↗

PubMedDate not supplied

An inference system based on fuzzy logic.

We present the use of fuzzy set theory for the management of imprecision and uncertainty. We first introduced fuzzy set theory according to two different perspectives: the logical and the possibilistic/probabilistic point of view. In addition, several examples of fuzzy sets in different contexts have been considered. The nature of imprecision in the measurement process has been investigated at various levels in order to identify different sources of uncertainty. The fuzzy inference system presented has proved to be a good tool for treating linguistic terms in a quantitative way. An application of a fuzzy inference system in computerized electrocardiography will be described. The main purpose of the present study is to show the potential use of fuzzy logic for the treatment of imprecision and uncertainty.

Adolescent↗

PubMedDate not supplied

A self-tuning effect of membership functions in a fuzzy-logic-based cardiac pacing system.

This paper describes a self-tuning method of membership functions in a fuzzy-logic-based cardiac pacing system and validates its feasibility in a double sensor system which has minute ventilation and oxygen saturation level as its guides for the rate regulation. Though the agreement between the pacing rates (fuzzy rates) calculated with three linguistic variables for each parameter and the target rates were not satisfactory, it was improved significantly by tuning the membership functions. Almost the same evaluated values with those obtained by using six linguistic variables for each parameter were obtained. Time required for the self-tuning process was about 40 s (386CPU, 20 MHz) which was fast enough for the system. The smaller number of linguistic labels results in a smaller number of rules, which is beneficial in implantable cardiac pacemakers with limited memory capacity. A fuzzy-logic-based cardiac pacing system is promising for the realization of custom-made cardiac pacemakers.

Exercise Test↗

PubMed2002

Efficiency of retrieval correlates with "logical" reasoning from causal conditional premises.

In two experiments, we examined the prediction that there should be a relation between the speed with which subjects can retrieve potential causes for given effects and their reasoning with causal conditional premises (if cause P, then effect Q). It was also predicted that when subjects are given effects for which there exists a single strongly associated cause, speed of retrieval of a second potential cause should be particularly related to reasoning with invalid logical forms--namely, affirmation of the consequent and denial of the antecedent. In the first experiment, 49 university students were given both retrieval tasks and conditional reasoning problems. The results were generally consistent with the predictions. The second experiment, involving 57 university students, replicated the first, with some methodological variations. The results were also consistent with the predictions. An analysis of the combined results of the two experiments indicated that individual differences in efficiency of retrieval of information from long-term memory did predict performance on the invalid logical forms in the predicted ways. These results strongly support a retrieval model for conditional reasoning with causal premises.

Adult↗

PubMed1991

Typicality in logically defined categories: exemplar-similarity versus rule instantiation.

A rule-instantiation model and a similarity-to-exemplars model were contrasted in terms of their predictions of typicality judgments and speeded classifications for members of logically defined categories. In Experiment 1, subjects learned a unidimensional rule based on the size of objects. It was assumed that items that maximally instantiated the rule were those farthest from the category boundary that separated small and large stimuli. In Experiment 2, subjects learned a disjunctive rule of the form "x or y or both". It was assumed that items that maximally instantiated the rule were those with both positive values (x and y). In both experiments, the frequency with which different exemplars were presented during classification learning was manipulated across conditions. These frequency manipulations exerted a major impact on subjects' postacquisition goodness-of-example judgments, and they also influenced reaction times in a speeded classification task. The results could not be predicted solely on the basis of the degree to which the rules were instantiated. The goodness judgments were predicted fairly well by a mixed exemplar model involving both relative-similarity and absolute-similarity components. It was concluded that even for logically defined concepts, stored exemplars may form a major component of the category representation.

Attention↗

PubMed2000

[Intraoperative control of mean arterial pressure and heart rate with alfentanyl with fuzzy logic].

OBJECTIVES: To describe a fuzzy logic controller that adjust alfentanil infusion during surgery based on changes in mean arterial pressure (MAP) and heart rate (HR). MATERIAL AND METHODS: We designed a fuzzy logic controller using if ... then ... conditions written in C language, to be executed by a 486 PC with a 66 Mhz CPU. The controller was used with eight ASA I-II patients undergoing gynecological surgery under anesthesia with propofol, alfentanil and ventilated with oxygen/air. MAP and HR were input every three minutes, after which the controller generated an infusion based on those figures. We performed a statistical study of alfentanil consumption time until extubation and time of hemodynamic stability. Relative error of MAP was calculated. RESULTS: The controller was used for a total of 373 min with the eight patients. MAP was 15% below the desired level for 2.14% (18 min) of that time and was 15% over the desired level for 5.6% (21 min) of the time. MAP held steady within the range of stability for the remaining 92.26% (334 min) of the time the controller was used. The relative error of MAP was 7.8 +/- 1.5%. Mean time until extubation was 7 min and 2 s. CONCLUSIONS: We believe the controller can be used to automate taks executed by experts. The controller was useful for stabilizing HR and MAP.

Adult↗

PubMed2000

Decision trees and fuzzy logic: a comparison of models for the selection of measles vaccination strategies in Brazil.

In 1997, health authorities of the state of São Paulo, Brazil designed a vaccination campaign against measles based on a decision model that utilized fuzzy logic. The chosen mass vaccination strategy was implemented and changed the natural course of the epidemic in that state. We have built a model using a decision tree and compare it to the fuzzy logic model. Using essentially the same set of assumptions about this problem, we contrast the two approaches. The models identify the same strategy as being the best one, but exhibit differences in the ranking of the remaining strategies.

Brazil↗

PubMed2001

Mental models and logical reasoning problems in the GRE.

The Graduate Record Examination (GRE) contains a class of complex reasoning tests known as logical reasoning problems. These problems are demanding for human reasoners and beyond the competence of any existing computer program. This article applies the mental model theory of reasoning to the analysis of these problems. It predicts 3 main causes of difficulty, which were corroborated by the results of 4 experiments: the nature of the logical task (Experiment 1), the set of foils (Experiment 2), and the nature of the conclusions (Experiments 3 and 4). This article shows how these factors can be applied to the design of new problems.

Educational Measurement↗

PubMed2002

Pathway logic: symbolic analysis of biological signaling.

The genomic sequencing of hundreds of organisms including homo sapiens, and the exponential growth in gene expression and proteomic data for many species has revolutionized research in biology. However, the computational analysis of these burgeoning datasets has been hampered by the sparse successes in combinations of data sources, representations, and algorithms. Here we propose the application of symbolic toolsets from the formal methods community to problems of biological interest, particularly signaling pathways, and more specifically mammalian mitogenic and stress responsive pathways. The results of formal symbolic analysis with extremely efficient representations of biological networks provide insights with potential biological impact. In particular, novel hypotheses may be generated which could lead to wet lab validation of new signaling possibilities. We demonstrate the graphic representation of the results of formal analysis of pathways, including navigational abilities, and describe the logical underpinnings of the approach. In summary, we propose and provide an initial description of an algebra and logic of signaling pathways and biologically plausible abstractions that provide the foundation for the application of high-powered tools such as model checkers to problems of biological interest.

Animals↗

PubMed2002

Comparison of conventional rule based flow control with control processes based on fuzzy logic in a combined sewer system.

While conventional rule based, real time flow control of sewer systems is in common use, control systems based on fuzzy logic have been used only rarely, but successfully. The intention of this study is to compare a conventional rule based control of a combined sewer system with a fuzzy logic control by using hydrodynamic simulation. The objective of both control strategies is to reduce the combined sewer overflow volume by an optimization of the utilized storage capacities of four combined sewer overflow tanks. The control systems affect the outflow of four combined sewer overflow tanks depending on the water levels inside the structures. Both systems use an identical rule base. The developed control systems are tested and optimized for a single storm event which affects heterogeneously hydraulic load conditions and local discharge. Finally the efficiencies of the two different control systems are compared for two more storm events. The results indicate that the conventional rule based control and the fuzzy control similarly reach the objective of the control strategy. In spite of the higher expense to design the fuzzy control system its use provides no advantages in this case.

Cities↗

PubMed2002

Fuzzy logic controller for weaning neonates from mechanical ventilation.

Weaning from mechanical ventilation is the gradual detachment from any ventilatory support till normal spontaneous breathing can be fully resumed. To date, we have developed a fuzzy logic controller for weaning COPD adults using pressure support ventilation (PS). However, adults and newborns differ in the pathophysiology of lung disease. We therefore used our fuzzy logic-based weaning platform to develop modularized components for weaning newborns with lung disease. Our controller uses the heart rate (HR), respiratory rate (RR), tidal volume (VT) and oxygen saturation (SaO2) and their trends deltaHR/deltat, deltaVT/deltat and deltaSaO2/deltat to evaluate, respectively, the Current and Trend weaning status of the newborn. Through appropriate fuzzification of these vital signs, Current and Trend weaning status can quantitatively determine the increase/decrease in the synchronized intermittent mandatory ventilation (SIMV) setting. The post-operative weaning courses of 10 newborns, 82+/-162 days old, were assessed at 2-hour intervals for 68+/-39 days. The SIMV levels, proposed by our algorithm, were matched to those levels actually applied. For 60% of the time both values coincided. For the remaining 40%, our algorithm suggested lower SIMV support than what was applied. The Area Under the Curve for integrated ventilatory support over time was 1203+/-846 for standard ventilatory strategies and 1152+/-802 for fuzzy controller. This suggests that the algorithm, approximates the actual weaning progression, and may advocate a more aggressive strategy. Moreover, the core of the fuzzy controller facilitates adaptation for body size and diversified disease patterns and sets the premises as an infant-weaning tool.

Area Under Curve↗